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MODULE III
Introduction to Process Integration
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Outline
1.
2.
3.
4.
5.
6.
Introduction
Foundation Elements
Case Study
Open Ended Problem
Acknowledgments
References
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TIER I
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1. Introduction
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1. Introduction
“Do your best;
then treat the rest”
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
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1. Introduction
Pollution is an ongoing concern
that has been addressed in many
different ways, from no pollution
control, end-of the-pipe treatment
(1970’s), Implementation of
Reuse/Recycle (1980’s) up to
Process Integration. The focus of
this module is to expose PI tools
for pollution reduction/elimination
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1. Introduction
What is Process Integration?
“It is a holistic approach to process
design, retrofitting and operation which
emphasizes the unity of the process”
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
8
Texas A&M University
1. Introduction
The use of PI methods started as early as 1970’s with
Pinch Technology (Heat Integration) in order to
optimize heat exchanger networks (HEN).
The moving force for mass integration was initially
pollution control; El-Halwagi and Manousiouthakis
(1989) proposed the use of mass exchange networks
(MEN) in analogy to the previously studied HEN.
PI tools can be used in a variety of industries and
with approaches as wide as those involving product
distribution, life cycle assessment etc (research in
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these an other areas is currently on their way)
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2. Foundation Elements
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2. Foundation Elements
2.1. Holistic approach of process
integration
2.2. Relationship of process integration to
process analysis
2.3. Overview of energy, mass and property
integration
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
Holistic: Emphasizing the importance of the
whole and the interdependence of its
parts. Concerned with wholes rather than
analysis or separation into parts
Heuristic: Of or constituting an educational
method in which learning takes place
through discoveries that result from
investigations made by the student
Source : http://dictionary.reference.com
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
Process Integration can address a wide set of design issues such as:
Efficient use of resources
and raw materials
Process
debottlenecking
Cost reduction
Other process
operation issues
Efficient use of
energy
Pollution
reduction
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
• Traditional process design has been addressed by heuristic
methods, based on experience or corporate preferences, in
which unit operations equipment have been design
individually.
• However little attention has been placed on the relationships
with other parts of the process
• Process Integration as a holistic approach, looks at the Big
Picture and the relationships among the different operations
and equipment alternatives
14
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
In order to illustrate how
Process Integration (PI)
can aid in the design
process an illustrative
example is given we have
3 options for a chemical
reactor
in
order
to
produce
a
chemical
product, the options to
choose from are:
Source : www.aiche.org/cep/ July 2001
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
Using a heuristic approach
the “best” option will be a
mechanically
agitated
vessel that produces
a
yield of 73.9% with a
volume of 12m3; however
is there any other way to
improve the process?
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
Two designs based on the same solution
Source : www.aiche.org/cep/ July 2001
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2. Foundation Elements
2.1 Holistic Approach of Process Integration
Using PI tools the following solution was
found, 96.9% yield and 9.93m3 of volume.
Two designs based on this solution are
shown next; the benefits of using PI tools
are evident.
However a thorough analysis of the
answer to the problem must be carried out
in order to find a feasible design based on
the findings obtained using a PI approach
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Source : www.aiche.org/cep/ July 2001
Texas A&M University
2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
•
In order to find solutions that include the relationship effects
among the different options for a given design task, the
engineer must use PI in order to find optimum answer to the
problems at hand, therefore PI tools should be included in the
process design structure. Seider, Seader and Lewin illustrate it
as shown in the next slides, for a complete description of the
design steps, referred to the above mentioned authors
•
Process design is a dynamic process, always making sure that
the solutions will agree with the constraints set by the
stakeholders
(management,
governmental
agencies,
environmentalist groups, general public etc) and the process
itself
19
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2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
Process Analysis
“Analysis of the process elements for
individual study of performance, by
using mathematical models and
computer simulators”
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
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Texas A&M University
2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
Current
Situation/Opportunity
Asses Primitive
Problem
(e.g. a new technology is
developed etc)
(Define the objective of the
design task based on the
identified opportunity)
Equipment Selection
(Assess different options
for the given process using
process
simulators,
spreadsheets, in house
software etc)
Preliminary Process
Synthesis, reactions,
Separation, T-P
Change Operations,
Task Integration
Survey Literature
(Identify all sources of
useful information for
the process design, e.g.
Handbooks etc)
Preliminary Data
Base Creation
(Thermodynamic data,
kinetics, toxicity etc)
Part I
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Source : Product and Process Design Principles : Synthesis, Analysis, and Evaluation W D. Seider J. D. Seader, D.R. Lewin
Texas A&M University
2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
No
Equipment Selection
(Assess different options
for the given process using
process
simulators,
spreadsheets, in house
software etc)
Is the Gross
Profit
Favorable?
Reject
Yes
Part I a
Part II
Part IV
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Source : Product and Process Design Principles : Synthesis, Analysis, and Evaluation W D. Seider J. D. Seader, D.R. Lewin
Texas A&M University
2. Foundation Elements
Create Process
Flow Sheet
Separation Train
Synthesis
Process Integration
Create
Detailed
Data Base
Pilot
Plant
Testing
Modify
Flow
Sheet
Prepare
Simulation
Model
Part I a
No
Go to
I or I a
Heat and Power
Integration
Part II
Yes
Is the Process
still Promising?
Second Law
Analysis
Part III
Qualitative
Synthesis
Flow Sheet
Controllability
Analysis
Dynamic Simulation
Part VI
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Source : Product and Process Design Principles : Synthesis, Analysis, and Evaluation W D. Seider J. D. Seader, D.R. Lewin
Texas A&M University
2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
Part I or I a
Yes
Is the Process
still Promising?
No
Detail Design,
Equipment Sizing,
Capital Cost
Estimation,
Profitability Analysis,
Optimization
Part III
Reject
No
Written Report,
Presentation
Part IV
Is the Process
still Feasible?
Part IV
Startup Assessment
(Additional Equipment,
Dynamic Simulation)
Reliability and Safety
Analysis (HAZOP, Pilot
Plant Testing etc)
Yes
Final Design
(P&ID, Bids etc)
Operation
Construction
Startup
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Source : Product and Process Design Principles : Synthesis, Analysis, and Evaluation W D. Seider J. D. Seader, D.R. Lewin
Texas A&M University
2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
Designing a new plant, retrofitting a existing one, has several operations
and for each operation different equipment options and configurations to
choose from.
The main problem is that the number of alternatives can be unmanageable.
If only heuristics are use for the design, the engineer will risk to miss the
true optimal solution to the design problem. Moreover, a design solution for
a given problem cannot be use for a different one, since the initial findings
are tailored for a specific problem.
Using a PI approach, one can avoid this issue, due to the fact that its
methodology can be applied to any problem. The PI methodology is
composed of three key components
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2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
Process
Synthesis
Process
Integration
It defines what
process units
and how they
should
be
interconnected
Process
Analysis
Analysis of the
process
elements
for
individual study
of performance
Process
Optimization
Minimizing
or
maximizing
a
desired function,
to find the best
option
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2. Foundation Elements
2.2. Relationship of Process Integration to Process Analysis
As it has seen, process
analysis is a step within the PI
methodology.
Preliminary
equipment
selection
$
It is important to emphasize
that PI will look at the
generalities rather than into the
details, and then the designer
can analyze the performance of
the solutions in order to
optimize his/her findings.
Impact
Spent
Committed
Equipment
required during
design
The following chart illustrate
the impact of the process
design steps over the budget
Process
Conceptual
Detailed
Plant
Detail Construction
Develop
Design
Design
Layout Mech.
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Startup &
Commission.
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Mass Integration
“Systematic methodology that provides a
fundamental understanding of the global flow of
mass within the process and employs this holistic
understanding in identifying performance targets
and optimizing the generation and routing of
species throughout the process”
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1 Mass Exchangers
•Mass Exchangers:
Lean Stream
(MSA) Flow
rate: Lj Inlet
Composition
Outlet
Composition
yiout
xjin
A mass exchanger is any directcontact mass transfer unit that
employs a MSA (Mass Separation
Agent), to remove selectively
certain component (e.g. pollutant)
from a rich phase (e.g. waste
stream).
The MSA should be partially or
totally immiscible in the rich phase
Mass
Exchanger
Outlet
Composition
xjout
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Rich (Waste)
Stream, Flow
rate: Gi Inlet
Composition
yiin
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1 Mass Exchangers
Lean
When the two phases are in
intimate contact the solutes are
distributed between the two phases
which leads to a depletion of solute
in the rich phase and enrichment of
the lean phase until equilibrium is
reached.
The difference in chemical potential
for the solute is the moving force
for mass transfer (Temperature
difference
for
heat
transfer,
Pressure
difference
for
fluid
movement etc)
Phase
Rich
Phase
Solute Transferred to lean phase
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Mass Exchange involve the following operations: Only counter
current operations will be consider because of their higher efficiency
Stripping
Adsorption
Leaching
Absorption
Extraction
Ion Exchange
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Adsorption:
Separation of a solute from a liquid or gaseous stream by contacting the
carrying phase with a small porous solid particles (adsorbent), usually
arranged in a packed bed. The adsorbent can be regenerated by desorption
using inert gas, steam etc
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Source : Université d’Ottawa / University of Ottawa - Jules Thibault
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
In order to select an adsorption column the designer must select a
suitable adsorbent for the given solute by looking at the appropriate
isotherm data as shown in the plot for a given set of process operation
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Source : Université d’Ottawa / University of Ottawa - Jules Thibault
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Absorption:
A liquid solvent is place in contact with a gas containing a solute to be remove by taking
advantage of the preferential solubility of the liquid. Reverse absorption is also know as
stripping (separation of a solute using a gas stream from a liquid phase)
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Source : Université d’Ottawa / University of Ottawa - Jules Thibault
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Liquid Extraction:
It employs a liquid solvent to remove a solute from another liquid by using the
preferential solubility of the solvent to the solute in the MSA
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Source : Université d’Ottawa / University of Ottawa - Jules Thibault
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Leaching:
Selective separation of some constituents
within a solid by contact with a liquid solvent
Mixing
Solvent
Solid
Slurry
Overflow
Solution
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Source : University of Ottawa - Jules Thibault
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Ion Exchange:
Cation/anion resins are used to replace undesirable anions
from a liquid phase by non hazardous ions
Ca
2
 Na2 R  CaR  2 Na
Cause of scale
forming impurities
Source : Université d’Ottawa / University of Ottawa - Jules Thibault
Water
softeners

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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
The mass exchanger is used to provide appropriate
contact of the lean and rich phase; there are two principal
categories of mass exchange units:
- Multistage (e.g. tray columns, mixer settlers etc), they
provide intimate contact follow by phase separation
- Differential (e.g. packed columns, spray towers and
mechanically agitated units), continuous contact between
phases without intermediate separation and re-contacting
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2. Foundation Elements
Tray Column
Heavy
Phase In
MSA
Out
Light Phase
Out
Multiple Mixers /
Settlers
Shell
Waste
In
MSA In
Perforated
Tray
Light Phase
In
Heavy
Phase Out
Multistage
Contactors
Waste 39
Out
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2. Foundation Elements
Spray Column
Light Phase
Out
Light Phase
Out
Mixer
Heavy
Phase In
Heavy
Phase In
Differential /
Continuous
Contactors
Heavy
Phase Out
Light Phase
In
Heavy
Phase Out
Light Phase
In
Mechanically Agitated
Mixer
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solute in the
rich phase
Equilibrium:
When a rich phase in a solute is put in contact with
a lean phase transfer of the solute to the lean
phase occurs, also part of the solute In the lean
phase also back transfer to the rich phase.
yi  f j ( x j )
*
At first the rate of solute being transfer from the
rich phase is bigger than the rate of solute back
transfer from the lean phase. However when the
concentration of solute in the lean phase
increases, the back transfer rate also increases.
Eventually the mass transfer rate and the back
transfer rates become equal and an equilibrium is
reached
(1)
Equilibrium
distribution
function
Maximum attainable
composition in the lean
phase
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
In environmental applications the engineer will find very often, diluted
systems which can be linearized over the operating range to yield:
yi  m j x j  b j
*
(2)
Special cases, Raoult’s Law for absorption
Partial
pressure at T
Mol fraction
of solute in
gas
P o solute(T ) *
yi 
xj
PTotal
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(3)
Mol fraction
of solute in
liquid
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Henry’s Law for stripping
yi  H j x j
*
Mol Fraction
of solute in
stripping gas
(4)
Mole fraction
of solute in
gas
So lubility
PTotal yi
Hj 
o
P Solute(T )
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(5)
Liquid phase
solubility of
pollutant at
temperature
T
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
For solvent extraction
yi  K j x j
Composition
of pollutant in
liquid waste
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Composition
of the solvent
*
(6)
Distribution
Coefficient
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2. Foundation Elements
The following relationships are used to size
multistage mass transfer exchangers:
yi,N+1= yiin
yi,1= yiout
yi,2
1
XJ,0= Xjin
yi,N-1
yi,3
2
XJ,1
yi,N
Gi
N-1
XJ,2
XJ,N-2
N
XJ,N= XJout
XJ,N-1
Lj
Overall Mass Balance:
Gi yi  L j x j  Gi yi
in
in
out
 Lj x j
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
out
(7)
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Rearranging (7):
Gi ( yi  yi
in
out
( yi  yi )
 out
Gi ( x j  x j in )
Lj
)  Lj (x j
out
 xj )
in
(8)
in
out
(9)
Eq. (8) represents the operating line in a McCabe-Thiele
diagram:
LJ / Gi
yiin
1
Operating
Line
Theoretical
stages
2
yiout
Equilibrium
Line
xJin
xJout
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
•The number of stages for a
multistage unit can also be
calculated with the following
equations, with NTP being the
number of theoretical plates
 m j Gi  yi in  m j x j in  b j 

 out
ln 1 
in
L j  yi  m j x j  b j 


NTP 
 Lj 
(10)


ln
m G 
 j i
in
out*

L j  xi  x j  Li 

 out
ln 1 

out* 



 m j Gi  xi  x j  m j Gi 
NTP 
 m j Gi 

ln 
 L 
 j 
yi  b j
in
(11)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
xj
out*

(12)
mj
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Texas A&M University
2. Foundation Elements
 Lj 



out
in
yi  m j x j  b j  m j Gi 
yi  m j x j  b j
in
in
NTP
(13)
When the contact time for each stage is not enough to reach
equilibrium, the number of actual plates (NAP) can be calculated
using contacting efficiency
NAP  NTP / o
(14)
Stage efficiency can be define on the rich or lean
phase, for the rich phase we have:
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
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Texas A&M University
2. Foundation Elements
 m j Gi  yi in  m j x j in  b j  m j Gi 

 out
ln 1 

in




L j  yi  m j x j  b j  L j 


NTP 

 m j Gi   
  1 
 ln 1   y 
 L 



 j   

(15)
For differential (continuous) mass exchangers, the height is
calculated using:
H  HTU y NTU y
(16)
H  HTU x NTU x
(17)
Based on rich phase
Based on lean phase
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
49
Texas A&M University
2. Foundation Elements
For mass exchangers with linear equilibrium:
yi  yi
NTU y 
*
( yi  yi ) logmean
in
( yi  m j x j
in
( yi  yi ) 
*
out
out
 b j )  ( yi
out
(18)
 m j x j  bj )
 ( yi  m j x j  b j ) 

ln  out
 ( y  m x in  b ) 
j j
j 
 i
in
out
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
in
(19)
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2. Foundation Elements
For mass exchangers with linear equilibrium (cont):
xj  xj
in
NTUx 
( x j  x j ) logmean
*
out
( x j  x j ) logmean
*
(20)
 out  yi in  b j   in  yi out  b j
   x j  
x j  
 m j  
 mj


 


in



y
out
  x   i  b j  
 j
 m j  

 
ln  
  in  yi out  b j  
 
 x j  
 m j  


 





(21)
51
Texas A&M University
2. Foundation Elements
 m j Gi  yi in  m j x j in  b j  m j Gi 

 out
ln 1 

in


L j  yi  m j x j  b j  L j  (22)


NTP 
 m j Gi 

1 
 L 
 j 
In order to calculate the diameter of the column
(m) we have:
Dmin
4(VFRA)

 ( MASVA)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(23)
52
Texas A&M University
2. Foundation Elements
In order to calculate the diameter of the column we need
volumetric flow rate of air (VFRA), maximum allowable
superficial velocity of air (MASVA):
 water   air
MASVA(m / s)  0.068
 air
(24)
To complete the design of a mass exchange unit, the designer
has to look into the costs that the unit will have. The total
annual cost (TAC) is given by:
TAC  AOC  AFC
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(25)
53
Texas A&M University
2. Foundation Elements
Where AOC is the annual operating cost and AFC is the annual
fixed cost of the unit. Recall equation (8)
Lean End of
Exchanger
Operating
Line
yiin
eJ
Driving
Force
Equilibrium
Line
yiout
xJin,max
xJin*
xJout
The number of mass exchange units will be higher for a small e, a vanishing driving
force. Therefore, it is necessary to assign a minimum driving force between the two
lines
54
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
We have:
yj
out. min
 m j (x j  e j )  bj
in
(26)
By using a minimum allowable composition difference, eJ the
designer can identify the minimum practically feasible outlet
composition of the waste stream
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
55
Texas A&M University
2. Foundation Elements
The number of mass exchange units will be higher for a small
e, a vanishing driving force. Therefore, it is necessary to assign
a minimum driving force between the two lines
Operating
Line
Rich End of
Exchanger
eJ
yiin
Equilibrium
Line
yiout
Remainder :
An outlet composition on
the equilibrium line =
infinite number of stages
xJ
in
xJ
out,max
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
xJ
out*
Driving
Force
56
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
We have:
y j  bj
in
xj
out. max

mj
e j
(27)
Where, eJ is the “minimum allowable composition difference”
and xJout,max is the maximum practically feasible outlet
composition of the MSA which satisfies the eJ driving force
As can be seen from (16 to 19) and (27), there is a trade off
between the driving force and the cost/size of the equipment to
be use for the separation. To illustrate the use of the previous
equations a example is given
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
57
Texas A&M University
2. Foundation Elements
Example 1
Air stripping is used to remove 95% of the rich
trichloroethylene (TCE, molecular weight = 131.4) dissolved in
a 200kg/s (3180gpm)
waste water stream. The inlet
composition of TCE in the waste water is 100ppm. Air (free of
TCE) is compressed to 202.6 kPa (2at) and diffused through a
packed stripper. The TCE-laden air exiting the stripper is fed to
the plant boiler which burns almost all the TCE.
Physical Data:
The stripping operation takes place isothermally at 293K and
follows Henry's law. The equilibrium relation for stripping TCE
from water is theoretically predicted using:
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
58
Texas A&M University
2. Foundation Elements
y j  0.0063x j
(28)
Where yi is the mass fraction of TCE in waste water and xJ is the mass
fraction of TCE in air. The air-to-water ratio is recommended by the
packing manufacturer to be:
24 m3Air / m3water
Stripper Sizing Criteria:
The maximum allowable superficial velocity of waste water in the
column is taken as 0.02m/s (approximately 30 gpm/ft2).The overall
height of transfer unit based on the liquid phase is given by:
HTUy = Superficial Velocity of waste water/Kya
59
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
Where ky is the water-phase overall mass transfer coefficient
and a is the surface area per unit volume of packing. The value
of Kya is provided by the manufacturer to be 0.002s-1
Cost Information:
The operation cost for air compression is basically the
electricity utility needed for the isentropic compression.
Electric energy needed to compress air may be calculated
using: Compression Energy (CE)
  1 




  Pout    
  
RTin
 


CE (kJ / kg)  
 1




   1  M airisentropic   Pin 


(29)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
60
Texas A&M University
2. Foundation Elements
The isentropic efficiency of the compressor is 60% and the electric
energy cost is $0.06/kWhr. The system is operated for 8000hr/y. The
fixed cost, $, of the stripper (including installation and auxiliaries, but
excluding packing) is given by:
Fixed cost of column = 4700HD0.9
Where H is the height of the column (m) and D is the diameter (m). The
cost of packing is $700/m3. The fix cost of the blower, $, is 12000LJ0.6,
where LJ is the flow rate of air (kg/s). Assume negligible salvage value
and a five year linear depreciation. (a) estimate the column size, fixed
cost and annual operating cost. (b) Due to the potential error in the
theoretically predicted value of Henry’s coefficient, it is necessary to
asses the sensitivity of your results to variation
61
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
of the value of Henry’s coefficient. Plot the column height,
annualized fixed cost and annual operating cost versus a the
relative deviation from the nominal value, for 0.5  a 2.0. The
parameter a is define by:
a = Value of Henry’s Coeffcient/0.0063
(c) Your company is planning to undertake extensive
experimentation to obtain accurate values of Henry’s
coefficient that can be used in designing and evaluating the
cost of this stripper. Based on your results, what would you
recommend regarding the undertaking of these experiments?
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
62
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Exhaust
Gas
xJout = ?
Waste Water
Gi = 200kg/s
yiin = 10-4
yiout
=
5*10-6
Boiler
Stripper
Stripping of
TCE from
Wastewater
Air, LJ = ?
xJin = 0
Blower
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
63
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: (a)
1. We will first have to calculate the flow and concentrations of
the different streams as follows:
 Air
PM air

RT
kg
2atm * 29
kg
kgmol

 2.412 3
3
m atm
m
0.082057
293K
kgmolK
kg
m3 Air
kgWater
1m3
kgAir
Li  2.412 3 * 25 3
* 200
*
 12.06
m
1m Water
s
1000kgWater
s
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
64
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Solution: Continuation
Using the overall mass balance equation we have:
12.06
1*10 4  5 *10 6

out
200
xJ
0
xJ
out
 0.00157 kgmol  phenol / kgmol  air
xJ
out
 1575 ppm
2. We now will calculate the height and diameter of the column,
superficial velocity of waste water (SVWW)
HTU y  SVWW / K y a
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
65
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: Continuation
HTU y
NTU y 
( yi  yi ) logmean
*
m
0.02
s  1m

0.02 s 1
100  5
*
( yi  yi ) logmean
(1*10 4  0.0063 * 0.00157)  (5 *10 6  0.0063 * 0)

 (1*10  4  0.0063 * 0.00157) 

ln 
6
 (5 *10  0.0063 * 0) 
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
66
Texas A&M University
2. Foundation Elements
Solution: Continuation
( yi  yi ) logmean  2.943 *105  29.43 ppm
*
NTU y 
100  5
 3.228
29.43
H  1* 3.228  3.228m
Dmin 
4(200 / 1000)
 3.568m
 (0.02)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
67
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: Continuation
3. With the equipment dimension we can proceed to calculate
the operating and fixed costs
 1.4 1 




 1.4  8.314 * 293   2  1.4 
CE (kJ / kg)  
 1  107.31kJ / kg

  

 1.4  1  29 * 0.6   1 


kJ 1kWhr $0.06
3
107.31 *
*
 $1.788 *10 / kg
kg 3600kJ 1kWhr
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
68
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: Continuation
Annual Operating Cost (AOC):
kJ
kg
s 8000hr
AOC  107.31 *12.06 * 3600
*
 $621,234.8 / year
kg
s
1hr
year
Equipment Cost (EC):
Stripper  4700(3.228 * 3.5680.9 )  $47,666.5

$
2
Packing  * (3.568m) * 3.228m * 700 3  $22,592.8
4
m
Blower  12000(12.06) 0.6  $53,455.2
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
69
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: Continuation
Fixed Cost (FC):
FC  47,666.5  22,592.8  53,455.2  $123,714.5
Solution: (b) (c)
Henry’s Law coefficient will affect the FC through the change in the
size of the system. By changing a one can find different values of
Henry’s Law coefficient and use them to calculate the size of the
column and then the FC; we will use Excel for this procedure. Since
we have a linear 5 year depreciation the FC will be divided by 5
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
70
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
Solution: Continuation
As the plot and Table 1 show,
there is a small change in the
TAC and AFC with changing
Alfa, meaning that we don’t
have appreciable savings by
changing the height of the
column with more accurate
values
of
Henry’s
Law
coefficient.
Therefore
the
project is not required; we just
saved our company a lot of
money!!!!
Alfa
Henry
H
AFC
TAC
0.5
0.00315
3.107112
24214.47
645449.3
0.75
0.004725
3.166444
24472.71
645707.5
1
0.0063
3.228434
24742.51
645977.3
1.25
0.007875
3.293275
25024.73
646259.5
1.5
0.00945
3.36118
25320.28
646555.1
1.75
0.011025
3.432384
25630.19
646865
2
0.0126
3.507149
25955.6
647190.4
71
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchangers
700000
600000
500000
400000
AFC
TAC
300000
200000
100000
0
0
0.5
1
1.5
2
2.5
Very slight
change
72
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
Mass Exchange
Networks
73
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
•MSA can be:
2.3.1. Mass Exchange Networks
They are Lean
Streams (Ns),
LJ, j = 1,
2…Ns
Mass
Separation
Agents (MSA)
Use to
remove
pollutants
from rich
streams, NR
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Process MSA, NSP
Low cost or almost free
“In plant”
External MSA, NSE
Must be bought
externally
74
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
Ns = NSP + NSE
(28)
Flow rates, stream concentration and target concentration of rich
streams are known, Gi, ySS, yit
Inlet compositions of lean streams are also known, xJS flow rate of
lean streams, LJ, is to be determine to minimize network cost
LJ  LJC
J = 1, 2…NSP
(29)
LJC is the flow rate of the Jth MSA available in the plant
75
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
Disposed
Comply with
Environmental
Regulations
Waste streams
can be
Forwarded to process
Sinks (equipment)
For recycle/reuse
Target composition
is the constraint
imposed by process
Sink
76
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
• Target composition are assigned by designer
based on the following constraints:
Physical
(e.g. maximum
Solubility of pollutant
In MSA)
Technical
(e.g. avoid corrosion,
Viscosity)
Safety
(e.g. stay away of
Flammability limits)
Environmental
(e.g. EPA, OSHA
Regulations)
Economic
(e.g. optimize cost
Of MSA regeneration)
77
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
• The following questions will arise:
What is the optimum
configuration?
How to match MSAs
to the waste streams?
Which MSA should be selected?
Which ME operation should we use?
78
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1. Mass Exchange Networks
• The previous questions will result in a
unmanageable number of combinations
• A systematic approach is required
“Targeting Approach”
79
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
Targeting Approach
“It is based on the
identification of
performance targets
ahead of design and
without prior commitment
to the final network
configuration”
80
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
Minimum
cost
of
MSA:
By
combining thermodynamic aspects
of the problem with cost data of the
MSA, the designer can identify the
minimum cost of the separation,
without designing the network
GENERALLY
INCOMPATIBLE
Minimum number of mass exchange
units: This objective is aim at
minimizing fixed cost of the system,
by doing so, one can reduce pipe
work, foundations, maintenance and
instrumentation
81
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
U = NR + Ni
(30)
U = Number of units
Ni = Number of independent synthesis sub-problems in
which original synthesis problem can be subdivided
•
In most cases there will be only one independent synthesis problem. In order
to avoid the incompatibility of the two targets, one have to use techniques that
will identify the MOC solution and then minimize the number of exchangers
that satisfy the MOC (Minimum Operating Cost)
82
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
eJ
yiin
yiout
Feasibility
area
xJin
•
•
xJout,max xJout*
In order for the separation to be feasible one have to work in the feasibility area
To relate the different concentrations in one scale, we need to use Equation
(27)
83
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
•
•
In order to minimize the cost of
external
MSA
one
must
maximize the use of in plant
MSA
Mass
Exchanged
Pinch
Point
The pinch diagram is a
graphical representation that
considers the thermodynamic
constraints of the system,
calculate MR with:
MRi  Gi ( yi  yi )
s
i  1,2,...., N R
t
(31)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
y
x1
84 x2
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
How to construct the pinch diagram?
1.
Represent each stream with an arrow
2.
Plot mass exchanged
composition
3.
Tail of the arrow is the supply
composition and head is target
composition
The slope is the flow rate of the stream
4.
versus
MRi
R2
its
5.
The vertical distance between the tail
and the head represent the amount of
pollutant transferred ( MRi ) from the
rich stream ( yi ) to the lean stream
6.
Stack the arrows on top of one another
starting with the one with the one
having the lower composition
R1
y1t
y2t
y1s
yi
y2s
85
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
How to construct the pinch diagram? MR
i
7.
Obtain the composite diagram by
using the “diagonal rule”
8.
The vertical axis is a relative scale,
one can move up and down the
curves while maintaining constant
the vertical distance
9.
10.
MR2
R2
MR1
Apply the same procedure for the
lean streams
Plot both composite curves in one
graph, slid the lean composite until it
touches the rich (waste) composite
stream
R1
y1t
y2t
yi
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
y1s
y2s
86
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
MSi
MS2
How to construct the pinch diagram?
y  b1
xj 
e
m1
S2
MS1
j
S1
(32)
11.
Use the above equation to obtain the
horizontal scale and Equation 33 to
calculate MS
yi
x1s
x1t
x2s
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
87 t
x
2
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
How to construct the pinch diagram?
MS j  L j ( x j  x j )
c
t
s
Mass
Exchanged
Excess Capacity
of Process
MSA’s
Lean
Composite
Stream
Rich
Composite
Stream
j  1,2...., N SP
(33)
Load to be
removed by
external MSA’s
yi
x1
88
x
2
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
How to construct the pinch diagram?
Integrated
exchange:
Mass
Exchanged
mass
Lean
Composite
Stream
Maximum amount
of pollutant that
can be transfer
•The Pinch point is the
minimum
feasible
concentration, it is also a
bottleneck, slid up or down
the composite curves until
they touch, keeping the
vertical distance and the
concentrations
Rich
Composite
Stream
Pinch
Point
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
yi
x1
89
x2
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
• In order to reduce the excess capacity of process MSA one can
either reduce flow rate, or composition. Care must be given
when choosing e, since it will cause the lean composite curve
to move to the right, increasing the load to be removed by
external MSAs
S j  Lj (x j
out
 xj
supply
)
(34)
Load of pollutant
above the pinch to
be removed
In the case that 2 or more
MSAs are overlapped, one
have
to
calculate
the
composition that will suit the
requirements of the plant and
compare the costs in order to
identify the MSA that will be
use in the separation
90
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
• To calculate cost of recirculation MSA (Cj)
and cost of removed pollutant (cjr) use:
C j  CM  CR  $ / kg recirculat ing MSA
Cost of Make up
cj 
Cj
r
(x j  x j )
t
s
Cost of
Regeneration
 $ / kg of removed pollutant
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(35)
(36)
91
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
•
1.
2.
3.
4.
There are cases when there are
no process MSAs, therefore a
different approach is required
in order to construct the pinch
diagram
MR
Draw the rich composite as
before
Draw the external MSA as Sj
arrows with the tail as the
supply composition and the
head its target composition
Calculate the cj
If arrow S2 lies completely to
the left of S1 and c2r < c1r
then eliminate S1
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Rich
Composite
Stream
S1
S2
S3
yi
x1
x2
92
x3
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
5.
6.
7.
8.
9.
If arrow S3 lies completely to the
left of S2 but c3r is > c2r then
retain both MSAs
In order to minimize the
operating cost of the network
one should use the cheapest
MSA where it is feasible
In this case S2 should be used
to remove all the rich load to the
left and the remaining load is
removed by S3
Calculate flow rates of S2 and S3
by diving the rich load remove
by the composition difference
for the MSAs
Construct the pinch diagram as
shown
MR
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Rich
Composite
Stream
S1
S2
S3
yi
x1
x2
93
x3
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Example 2
A process facility converts scrap tires into fuel via pyrolisis. The
discarded tires are fed to a high temperature reactor where heat breaks
down the hydrocarbon content of the tires into oils and gaseous fuels.
The oils are further processed and separated to yield transportation fuels.
The reactor off gasses are cooled to condense light oils. The condensate
is decanted into two layers: organic and aqueous. The organic layer is
mixed with the liquid products of the reactor
The aqueous layer is a waste water stream whose organic content must
be reduce prior to discharge. The primary pollutant in the waste water is a
heavy hydrocarbon. The data for the waste water stream is given in the
next slide. A process lean stream is a flare gas (a gaseous stream fed to
the flare) which can be used as a process stripping agent. To prevent
back propagation of fire from the flare, a seal pot is used.
94
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
Stream
Description
Flowrate
Gi
kg/s
Supply
Composition
(ppmw)
yis
Target
Composition
(ppmw)
yit
R1
Aqueous
layer from
decanter
0.2
500
50
Table 1
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
95
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Example 2, Continuation
An aqueous stream is passed though the seal pot to form a buffer zone
between the fire and the source of the flare gas. Therefore, the seal pot
can be used as a stripping column in which the flare gas strips the
organic pollutant off the waste water while the waste water stream
constitutes a buffer solution preventing back propagation of fire. Three
external MSAs are considered: a solvent extract S2, an adsorbent S3 and a
stripping agent S4. The equilibrium data for the jth MSA and the process
MSA are given in the next slide, the equilibrium data is given by
yi = mjxj
Where yi and xj are the mass fractions of the organic pollutant in the
waste water and the jth MSA, respectively. Use the pinch diagram to
determine the minimum operating cost of the MEN
96
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Example 2, Continuation
Stream
mJ
eJ
CJ
$/kg
MSA
900
0.5
200
-
300
1000
1.0
100
0.004

10
200
0.8
50
0.030

20
600
0.2
50
0.050
Upper Bound
on flow rate
Supply
composition
(ppmw)
Target
Composition
(ppmw)
kg/s
xs J
xJ t
S1
0.15
200
S2

S3
S4
Ljc
Table 2
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
97
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
To atmosphere
Example 2, Continuation
Gaseous
Fuel
Flare
Condenser
Reactor
Off Gases
Decanter
Light oil
Water
Waste water
R1
Separation
Shredded
Tires
Pyrolisis
Reactor
Seal Pot
To waste
water
Flare Gas
S1
Finishing
Liquid Fuel
98
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
To atmosphere
2.3.1.1. Mass Exchangers
Solution
Gaseous
Fuel
Condenser
Reactor
Off Gases
Decanter
Waste
water R1
Light oil
Separation
Shredded
Tires
Pyrolisis
Reactor
Flare
S2 S3 S4
MEN
To waste
water
Flare Gas,
S1
Finishing
Liquid Fuel
99
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.1. Mass Exchangers
Solution, Continuation
Calculate and plot the pinch diagram, using Equations 31,32,33 and Tables 1 and 2
R1
S1
MR
y
0
50
90
500
0
200
105
550
Mass
Exchanged
10-6
200
Pinch Diagram
150
S1
100
R1
S1
MR
y
0
50
90
500
90
200
195
550
50
R1
0
0
100
200
300
y. ppmw
400
500
100
600
Texas A&M University
2. Foundation Elements
Solution, Continuation
Mass
Exchanged
10-6
Pinch Diagram
Pinch
Point
140
120
Excess Capacity of Process
MSA
100
80
Integrated
Mass
Exchanged
60
New S1 Target
Composition
40
20
Mass to be Removed by External MSA
0
0
100
200
300
y. ppmw
400
500
600
101
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Solution, Continuation
• From the pinch diagram the load to be removed by the
process MSA is 64 x 10-6 kg/s, the excess capacity is 45 x 106 kg/s; we have to use the whole flare gas flow rate to
remove pollutant from the waste water, due to the fire
hazard that it represents (we cannot by pass part of it
directly to the flare, in order to reduce the excess capacity)
from a mass balance or the pinch diagram we find the outlet
composition of S1 to be: 400 ppmw
• We now have to evaluate the different external MSAs. The
load to be removed by external MSA is approximately 31 x
10-6 kg/s, we need to check the thermodynamic feasibility of
each external MSA
102
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Texas A&M University
2. Foundation Elements
Solution, Continuation
103
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2. Foundation Elements
Solution, Continuation
Mass
Exchanged
10-6
Pinch Diagram
200
150
100
50
0
0
S4
48
100
S3 10
20
200
200
600
300
y. ppmw
400
S2 300
500
600
1000
104
Texas A&M University
2. Foundation Elements
Solution, Continuation
• Calculating the costs of each separation agent,
using Equation 36:
c2r = 5.714 $/kg
c3r = 157.89 $/kg
c4r = 86.20 $/kg
Analysis: S2 is not a feasible MSA since its target concentration is higher
that the target concentration of the rich stream therefore mass transfer is
not possible. S4 is the selected MSA, flow is 31x10-6kg/s annual operating
cost is 31x10-6x86.2x3600x24x365 = $84,270.5/yr
105
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
•
Energy In
Process integration is conformed of mass and
energy integration
Process
Mass Out
Mass In
•
In order to achieve a good mass integration,
one has to set targeting goals; from an overall
mass balance:
Energy Out
Mass In  Generation  Mass Out  Depletion
(37)
106
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
•
In order to reduce intake of fresh resources and reduce the discharge
of waste streams one need to consider recycle, mixing, segregation
and/or interception. In order to identify the recycle (direct or after
segregation/interception) strategy that will have a net effect on the
system the following procedure follows
Fresh Load
FLk,1
FLk,2
FLk,1
Terminal Load
1
4
2
3
TLk,1
TLk,2
5
TLk,3
No Recycle
TLk,4
107
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
•
Identify where recycle of streams will have the biggest net effect
Terminal Load
Fresh Load
FLk,1
FLk,2
FLk,1
1
4
2
3
TLk,1 + Rk,2 – Rk,1
TLk,2 - Rk,2
5
TLk,3
TLk,4
No Net effect = Poor Recycle
+ Rk,1
Rk , 2  Rk , 2  Rk ,1  Rk ,1
108
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
Terminal Load
Fresh Load
FLk,1 – Rk,2
1
FLk,2 – Rk,1
2
FLk,1
3
TLk,1 – Rk,1
4
TLk,2 – Rk,2
5
TLk,3
TLk,4
 Rk , 2  Rk ,1
 Rk , 2  Rk ,1
Effective Recycle from Terminal Streams
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
109
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
Terminal Load
Fresh Load
FLk,1 – Rk,2
1
FLk,2 – Rk,1
2
FLk,1
3
4
TLk,1 – Rk,1
TLk,2 – Rk,2
5
TLk,3
TLk,4
 Rk , 2  Rk ,1
 Rk , 2  Rk ,1
Effective Recycle from Terminal and Intermediate Streams
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
110
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
•
Recycle of streams must comply with sink constraints; such as composition and flow rate
which a sink can take. In order to take advantage of direct recycle opportunities within a
plant one has to identify them by using a graphical technique know and the source/sink
mapping diagram
•
Effective recycle should connect fresh
intake and out streams
Acceptable
Composition
Range
kg/s
Source
Flow Rate Load,
Acceptable
Flow Range
Sink
Pollutant Composition
111
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
•
The interception of the two constraints is the area where any source
within it can be recycled directly to the sink
•
The maximum amount to be recycle is
the minimum between the fresh inlet
and outlet load. In order to recycle b
and c use the mixing arm rule
Direct recycling does not require new
equipment
•
Define equipment constraint from,
technical data, operation conditions,
physical and chemical properties etc
a
Flow Rate Load, kg/s
•
Sink
Source
S
b
Pollutant Composition
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
c
112
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
• Arm rule:
Fs  Fb  Fc
ys 
•
Flow Rate
(38)
Fc yc  Fb yb
Fc  Fb
Load, kg/s
Resulting Mixture
Fs
(39)
Fb
b
Fc
c
If a fresh source is mixed with
a polluted one, in order to
minimize the use of fresh one
has to minimize fresh arm
yb
ys
yc
Sources
Pollutant
Composition
113
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.2. Targeting rules
• Note:
1. The previous method can be simplified for a complex
plant since no all equipment will required fresh
utilities or discharge waste streams. We will identify
those that do and apply the previous method
2. Identifying equipment constraints can reduce fresh
and waste streams with little process modifications,
by working with minimum requirements
114
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
The pinch diagram is a very useful tool, however it has accuracy limitations common
to any graphical method, therefore an algebraic approach that will overcome these
limitations is presented
• The Composition-Interval Diagram (CID)
This diagram shows the mass exchanged between the
thermodynamically feasibility and the location of the pinch point
different
streams,
The number of scales is equal to Nsp + 1, where Nsp is the number of lean streams.
Each process is represented by a vertical arrow with supply and target compositions
as the tail and head respectively. The horizontal lines are the composition intervals
whose number is define as:
Nintervals  2( N R  N SP )  1
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
(40)
115
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2. Foundation Elements
116
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• Within each interval it is possible to transfer mass from the rich
stream to the lean stream and it is possible to transfer mass from
the interval to any MSA that is in an interval below it
Table of Exchangeable Loads (TEL)
• The TEL is used to determine the load of mass exchanged within
each interval; for the waste stream the load is:
Wi,kR = Gi(yk-1 – yk)
(41)
And the exchangeable load for the lean streams is:
Wj,kS = Ljc(xj,k-1 – xj,k)
(42)
117
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• Since one or more streams will pass through one or more intervals
we can express the total load of the stream that passes through
that interval k; for the waste and lean streams we have
W   i passes through intervalk  W
(43)
WkS   j passes through intervalk  W jS,k
(44)
R
k
R
i ,k
118
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• Note that mass can be transferred within each interval from a
waste stream to a lean stream, as a result it is possible to
transfer mass from a waste stream in a interval to a lean
stream in a lower interval, the resulting mass balance is:
WkR   k 1  WkS   k
(45)
 k 1 ,  k are the residual mass of pollutant entering
and leaving the kth interval
119
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• The graphical representation is:
 k 1
Waste
Recovered from
Waste Streams
W
Residual Mass from
Preceding Interval
R
k
Residual Mass to
Next Interval
K
S
k
W
k
Mass
Transferred to
MSA’s
120
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
Note:
• Initial residual mass for k = 0 is zero
• The most negative value of the residual mass load
indicates the excess capacity of MSA’s, in order to
reduce it, one can either reduce the flow rate, or the
composition of the MSA’s, one this is done one needs to
recalculate and apply the previous procedure. The pinch
will be represented at the location when the residual
mass is zero. This result will be equal to the one given
by the pinch diagram
• After reducing flow rate or concentration, the remaining
load is the load to be removed but external MSA’s
121
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
Example 3
A lean MSA will be used to reduce
the composition of a rich stream,
the data is give in the table
•Calculate the number of intervals
•Calculate the compositions of
each stream for the y and x scales
N Intervals  2(1  1)  1
•Prepare de CID diagram
•Calculate a TEL table, using 41,
42
•Calculate the cascade diagram,
by 43,44
N Intervals  3
122
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
Composition Table
123
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
CID Table
124
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
TEL Table
125
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Cascade Diagram
126
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• The excess capacity of the MSA is 0.000027
kg/s of pollutant and the actual flow required for
the separation is:
LActual Flow
LActual Flow
Excess Capacity (45)
 Li 
t
s
x x
0.000027
 0.15 
 0.111
127
0.0009  0.0002
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
• Recalculating the TEL and cascade diagram
128
Pinch
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.3. Synthesis of MEN, Algebraic Approach
•The concentrations at which the pinch point is
located are:
y = 0.00011
x = 0.0002
The quantity leaving the bottom of the cascade
diagram is the amount to be removed by external
MSA’s, 0.00001 kg/s
129
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.4. Synthesis of MEN, with Minimum Number of Exchangers
• In order to minimize the number of mass exchangers to
obtain a MOC solution, we will decompose the design
problem in to two sub-problems one above and one
below the pinch
U MOC  U MOC, above pinch  U MOC, below pinch
(46)
U MOC, above pinch  N R , above pinch  N S , above pinch  N i , above pinch
U MOC, below pinch  N R , below pinch  N S , below pinch  N i , below pinch
130
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.5. Feasibility Criteria
• By starting the synthesis of mass exchangers at the pinch
point one can ensure that the options will not be compromised
at later steps, due to the fact that the pinch point the all
streams match at the minimum driving force e. The matching of
streams will be done in two sections, above and below the
pinch, two criteria must be applied to ensure feasibility
Stream
Population
N RAbove  N L Above
(47)
N LBelow  N RBelow
(48)
131
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.5. Feasibility Criteria
• If the previous inequalities do not hold with the rich and
lean streams/branches then splitting of one or more of
them is required, as before stream splitting might be
required to comply with the following inequalities
Lj
Thermodynamic
Feasibility
mj
Lj
mj
 Gi Above Pinch
(48)
 Gi Below Pinch
(49)
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
132
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
Example 4
• The following example
will
illustrate
the
procedure for network
synthesis;
given
a
process with two waste
streams and two process
MSA’s
133
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• The composition for waste and lean
streams are shown in the table
• Number of Intervals = 7
• Calculate the CID
• Calculate TEL
• Revise TEL
134
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• CID
135
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• TEL
136
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2. Foundation Elements
• Cascade Diagram
137
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• The excess load of the MSA’s is 0.00151kg/s;
using Equation 45 and reducing the excess
capacity of S2 we have an actual flow of
2.925 kg/s and a revise TEL and cascade
diagram can be calculated, with its pinch
point at interval 4 and compositions y, x1, x2 =
0.0165, 0.00725, 0.01, respectively
138
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2. Foundation Elements
• TEL, revised
139
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• We will now define the number of mass exchangers
• Define feasibility criteria
• Match streams
U MOC, above pinch  2  2  1  3
U MOC, below pinch  2  1  1  2
140
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2. Foundation Elements
• Cascade Diagram, revised
Pinch Point
141
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
•
The following figure will aid during checking of the feasibility criteria
R1
S2
S1
R2
Pinch
Point
G1 = 2.5 kg/s
G2 = 1 kg/s
L1/m1 = 2.5 kg/s
L2/m2 = 1.95 kg/s 142
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
N RAbove  N L Above
22
Lj
mj
 Gi Above Pinch
Match:
R1 – S1
R2 – S2
143
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
Mass Exchanged Loads
R1 = 0.08375 kg/s
S1 = 0.03875 kg/s
Mass exchanged = 0.03875 kg/s
R2 = 0.0135 kg/s
S2 = 0.0585 kg/s
Mass exchanged = 0.0135 kg/s
144
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
•Remaining load from R1 = 0.045 kg/s
•Excess capacity of S2 = 0.045 kg/s
Note that these values are equal, due to the fact
that there is no mass transferred trough the pinch.
Now we proceed to match exchangers
represented by circles with streams; the mass
exchanged appears within the circles and
composition in arrows. Load to be removed by
external MSA is 0.0155kg/s
145
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
R1
2.5 kg/s
0.05
0.045
S1
0.045
1 kg/s
0.03
x1 *
R1 capacity
not removed
by S1
x2 **
0.0135
0.0135
0.0165
S2 can
remove
load
0.03875
0.03875
R2 transfers
all its load
5 kg/s
0.015
R2
S2
0.0165
0.00725
0.01
S1 is
depleted
146
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
• In order to calculate the intermediate
compositions leaving exchanger R2 – S2
use a material balance using Equation 37:
x2 ** = 0.01 + 0.0135/3 = 0.0145
x1* = 0.05 - 0.045/2.5 = 0.032
147
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
•After completing the network design above the pinch we will
proceed to do the same below the pinch
N LBelow  N RBelow
1 2
R1
Pinch
Point
R2
S1
S3 External MSA
148
G1 = 2.5 kg/s
G2 = 1 kg/s
L1/m1 = 2.5 kg/s
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
Checking feasibility (Eq. 49) determines that S1 has to be split in two since
L1/m > Gi. There are many different combinations in order to achieve it, for
this case we will split them arbitrarily and match the streams
G1 = 2.5 kg/s
G2 = 1 kg/s
S3 External MSA
L12/m1 = 0.725 kg/s
Pinch
Point
S1
R2
L11/m1 = 1.775 kg/s
R1
L1= 5 kg/s
149
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
Lj
mj
Match:
 Gi Below Pinch
•
Mass Exchanged Loads
•
•
•
R1 = 0.01625 kg/s
S11 = 0.0079875 kg/s
Mass exchanged = 0.0079875 kg/s
•
•
•
R2 = 0.0105 kg/s
S12 = 0.0032625 kg/s
Mass exchanged = 0.0032625 kg/s
R1 – S11
R2 – S12
150
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.1.6. Network Synthesis
•Remaining load from R1 = 0.0082625 kg/s
•Remaining load from R2 = 0.0072375 kg/s
•In order to remove the remaining load from
waste streams it is required to use external
MSA’s (S3)
151
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2. Foundation Elements
S3 External MSA
G1 = 2.5 kg/s
R1
G2 = 1 kg/s
S1
R2
Pinch
Point
0.079875
0.0079875
0.0032625
0.0032625
0.0082625
0.0082625
L1= 5 kg/s
0.0072375
0.0072375
Calculate the
Intermediate
Compositions
Can you
Suggest another
Configuration
for S3?
152
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R1
R2
2.5 kg/s
0.05
S2
1 kg/s
0.03
0.045
0.045
x2 **
S1
x1 *
0.0135
0.0135
0.03875
0.03875
0.0165
0.0165
5 kg/s
0.015
0.01
0.00725
Pinch
Point
0.079875
0.0079875
0.0032625
0.0082625
0.0032625
0.0082625
L1= 5 kg/s
0.0072375
S3
0.0072375
Complete
Network
153
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
Heat Exchange
Networks
154
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Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
Cold Streams In
•
Hot
Streams
Out
Every plant requires energy
to be transfer from a hot
stream to a cold one; hence
the importance a proper
heat exchange network in
order to have a positive
impact in the economics
and operation
of
any
process
Heat Exchange
Network
Hot
Streams In
Cold Streams Out
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2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
•
To define the HEN (Heat Exchange Network) problem first we need to
define the following:
A number of hot process streams that need to be cooled NH and a number
of cold process streams that need to be heated NC, we need to
synthesize a network that will achieve the transfer of heat at minimum
cost
For hot streams the heat capacity can be expressed as:
Heat Capacity  FCP ,u
(50)
Supply Temperatur e  Tus
Target Temperatur e  T
t
u
For u = 1,2,…NH
156
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2.3.2. Heat Integration
In addition for the cold streams we have:
Heat Capacity  fc P ,v
(51)
Supply Temperatur e  t
s
v
For v = 1,2,…NC
Target Temperatur e  t tv
A number of cold and hot streams is available whose supply and
target temperatures are known but not their flow rates. In order to
design a HEN the following questions need to be answered:
157
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2.3.2. Heat Integration
What is the
Optimal configuration
How should the hot and
Cold streams be matched?
What is the optimal heat load to be
removed/added by each utility?
Which heating/cooling utilities should be used
158
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• In order to have heat transfer between two
streams the following relationship will
established a correspondence between
the hot and cold streams temperature:
T  t  T
min
(52)
159
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• A special case of mass exchanged is the
one that compares the heat exchanged
problem corresponding T, t, Tmin with yi,xj
and ej respectively, and having mj, bj equal
to zero
160
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2.3.2. Heat Integration
NOTE:
The order of X and Y axis
used here are different
from
what
has
been
commonly used in the
literature. The reason is
that there is a strong
interactions between mass
and energy making the
enthalpy expression non
linear
function
of
temperature therefore it is
easier to have enthalpy in
function of temperature,
this specially important
when combining mass and
heat integration
HE
T v. H
Approach
T
T min
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
T
HE vs. T
Approach
161
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2.3.2. Heat Integration
• The procedure use to set up the pinch diagram is exactly the
same as the one use for mass integration, by placing the hot
and cold streams temperatures in the diagram, starting by their
supply temperature as the tail of an arrow and the target
temperature as the head of an arrow. The following equation
can be used to calculate the vertical distance or heat loss by
the hot stream
HH u  Fu CP,u (T  T )
s
u
t
u
(53)
162
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• And for the heat gained by the cold stream we have:
HCv  f v cP,v (t  t )
t
v
s
v
(53)
• To construct the pinch diagram we have:
163
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2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
HE
HE
HH2
HC2
C2
H2
HH1
HC1
C1
H1
T1t
T2t
T1s
T2s T
T
t1
t
t2
t
t1
s
t = T - Tmin
Source : Pollution Prevention through Process Integration, M. M. El-Halwagi
t2
164
s
Texas A&M University
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2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
How to construct the pinch diagram?
Heat
Exchanged
Minimum
Heating Utility
Cold
Composite
Stream
Integrated Heat
Exchange
Minimum
Cooling Utility
Thermal
Pinch Point
Hot
Composite
Stream
T
t = T - Tmin
165
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
The analysis of the thermal pinch diagram is as follows:
• The cold composite curve cannot be slid down any further
otherwise there will not be thermal feasibility, if the cold
composite is moved up less heat integration is possible
therefore more utilities are required
• Above the pinch there is a surplus of cooling and below the
pinch there is a surplus of heating utilities
166
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2.3.2. Heat Integration
• A similar analysis as the one used for mass integration can be
done in order to apply an algebraic cascade diagram, the
number z of intervals is:
Nint  2( N H  NC )  2
(54)
• To construct a Table of Exchangeable Heat Load TEHL we
need:
HH u , z  Fu CP ,u (Tz 1  Tz )
(55)
HC v , z  fc p ,v (t z 1  t z )
(56)
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167
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• The collective total load for the hot and cold process
streams are:
HH
HC
Total
z
  u passes through intervalHH u , z
Total
z
  v passes through intervalHC v , z
(57)
z, where u 1, 2 ,... N H
(58)
z, where v 1, 2 ,... N C
168
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• As it was mentioned for mass exchanged, it is feasible to
transfer heat from a hot process stream to a cold one within
each temperature interval, a heat balance around a temperature
interval yields:
Residual Heat from
Preceding Interval
rz 1
HH
Heat Added by
Total
z
Process Hot
Stream
Heat Removed
by Process Cold
Stream
Z
HC
Residual Heat to Next
Interval
rz
Total
z
169
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2.3.2. Synthesis of MEN, Algebraic Approach
• The resulting heat balance is:
rz  HH
Total
z
 HC
Total
z
 rz 1
(59)
170
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2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.2. Heat Integration
• The resulting TID is:
171
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
Property Integration:
“Functionality based holistic approach to the
allocation and manipulation of streams
and processing units which is based on
tracking, adjustment, assignment and
matching of functionalities throughout the
process”
172
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
• Component mass balances are an integral
part of process design. There are several
design problems in which the designer is
interested in a group of properties such as
viscosity, corrosion, density etc. Solvent
selection is a clear example in which one is
interested in its volatility, viscosity, equilibrium
distribution,
instead
of
its
chemical
constituents.
173
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
• Property visualization tools are limited to 3 properties, an
algebraic approach is used to deal with more complex
cases. The advantage of visualization tools is based on
the insides that give of the process, and how the design
problem can be addressed. In order to apply this method
to a set of properties we need to introduced the concept
of cluster
• Properties are not conserved, as a result they cannot be
tracked among units without using mass balances, the
problem is that often is not possible to identify every
single chemical species e.g. Gasoline, Dowtherm
174
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2.3.3. Property Integration
Cluster
“Defines as condensed surrogate properties
which can be used to characterize the
complex mixture and can be tracked my
mapping the raw properties of infinite
compounds onto finite domains”
175
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
•
The problem statement is: given a number of process streams Ns
which contain the chemical species of interest, can be used in a
number of sinks Nsinks (process units) in order to optimize a a desired
objective e.g. minimize usage of fresh resources, maximize use of
process resources, minimize cost of external streams etc. Each sink
has a set of constraints defined as:
propertymin  pi ,sin k  propertymax
Flow Ratemin  Flow ratesin k  Flow Ratemax
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2.3.3. Property Integration
• Each stream can be characterized by Nc raw properties
with a mixing rule that characterized a given stream
 i ( p i )   sN1 xs i ( pi , s )
s
(60)
xs  Fractional contribution of the s th stream
to the total flow rate
 i ( pi , s )  Operator of pi , s
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2.3.3. Property Integration
• pi,s can be normalized as:
 i ( pi ,s )
i , s 
ref
i
(61)
• An augmented property index (AUP) for each stream s, is define as
the summation of the dimensionless raw property operators:
AUPs   i , s
Nc
i 1
s  1,2,..., N s
(62)
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2.3.3. Property Integration
• Ci,s is the cluster for property i in stream s
Ci ,s 
i , s
(63)
AUPs
• For any stream s, the sum of clusters must be conserved adding
up to a constant e.g. unity
 Cs  1
Nc
i 1
s  1,2,..., N s
(64)
Ci  
Ns
s 1
 s Ci , s
s  1,2,..., N c
(65)
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2.3.3. Property Integration
•
The framework for allocation and interception for property integration is:
u=1
s =1
.
Property
Integration
Network (PIN)
.
.
s =1
u=2
.
.
.
Processed
Sources
(back to
process)
u = Nsinks
Sources
Segregated
Sources
Sinks
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2.3.3. Property Integration
•
Consider a cluster of stream s to unit u, with three targeted properties i, j, k we
have:
Ci , s 
C j ,s 
i ,s
i ,s   j ,s   k ,s
 j ,s
i,s   j ,s   k ,s
1

1

 j ,s
i ,s
 k ,s

i ,s
(66)
1
i ,s
 k ,s
1
 j ,s
 j ,s
(67)
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Ck , s 
•
i ,s
i,s   j ,s   k ,s

1
 j ,s
i ,s

1
 k ,s  k ,s
(68)
In order to obtained an overestimation of the feasibility region we have:
max
C i ,s
1

 j ,s
min
1
 i ,s
max
 k ,s
min

 max
i ,s
(69)
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2.3.3. Property Integration
min
C i ,s
1

1
C j ,s 
 j ,s
min
 i ,s

 i ,s
min
 j ,s
min
C j ,s

 k ,s
 j ,s
min
1
 i ,s
min
 j ,s
 i ,s
min
1
max
max
min
1
min
•
min
 k ,s
min
(70)
(71)
max
C k ,s

 i ,s
1
min
 k ,s
max
 k ,s
min

(72)
 max
j ,s
1
 min
k ,s
 k ,s
max
(73)
1
In order to allocate, mix or intercept streams one needs to identify a
feasibility region for the sinks, by using the following relationships:
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2.3.3. Property Integration
C k ,s 
min
 i ,s
min
 k ,s
min
•

1
 min
j ,s
 k ,s
min
(74)
1
These points will now need to be plotted in a ternary diagram will be shown next
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2.3.3. Property Integration
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Ci
2.3.3. Property Integration
We need to find the true
estimation of the feasibility
region (for a more detailed
explanation of how to obtained
these
results,
review
the
references at the end of the
module)
Cj,s
Overestimated
Region
min
Ci,smax
Cj,smax
Cj,smin
Cj
Ck,s
min
Ck,smax
Ck
186
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2.3.3. Property Integration
Ci
True Region
min
min
(imax
,

,

,s
j ,s
k ,s )
min
max
(imax
,

,

,s
j ,s
k ,s )
max
min
(imax
,

,

,s
j ,s
k ,s )
min
max
(imin
,

,

,s
j ,s
k ,s )
max
min
(imin
,

,

,s
j ,s
k ,s )
Cj
Ck
( ,  ,  )
min
i,s
max
j ,s
max
k ,s
187
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2.3.3. Property Integration
•
In order to plot these diagrams in a spread sheet, we need to related this
ternary coordinates in a X vs. Y plane as follows:
Ci
Y
(0.866, 0.50)
S
Ys
Ci,s
(1, 0)
(0, 0)
Cj
Xs
(cos

3
)Ci , s
Ck
X
188
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2.3.3. Property Integration
•
The equations that relate X vs. Y with ternary coordinates are:
Ys  (sin

3
)Ci , s  0.866Ci , s 
0.866i , s
i , s   j .s   k , s
(75)
0.5i , s   k , s

X s 1  C j , s  (cos )Ci , s  1  C j , s  0.5Ci , s 
3
i , s   j .s   k , s
(76)
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2.3.3. Property Integration
•The next step is to set up optimization rules as follows:
Relating cost to fractional contribution of sources
Consider two sources s and s+1 that are mixed to satisfy sinks constraints,
let xs and xs+1 denote the fraction contribution of sources s and s+1 to the
total flow rate of the mixture. Let s be more expensive than s+1, as
Costs>Costs+1, therefore we have:
Costmixture = xs (Costs – Costs+1) + Costs+1
(77)
From the previous equation we can conclude that in order to minimize the
cost of the mixture xs must be minimized
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
Rule No. 1
“When two sources (s and s+1) are mixed
to satisfy the property constraints of a sink
with source s being more expensive than
s+1, minimizing Costmixture is achieved by
selecting the minimum feasible value of xs”
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2.3.3. Property Integration
Derivation of relationships between minimum cluster
arms (s) and minimum fractional contribution xs
xs cannot be visualized in a ternary diagram, the lever
arm on the ternary cluster diagram represents another
quantity defined as s, to relate both quantities the AUP is
described by equation 62
AUPs
 s  xs
AUP
AUP   sNs1 xs AUPs
(78)
(79)
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Rearranging we have:
 s AUPs 1
xs 
 s AUPs 1  (1   s ) AUPs
(80)
Taking the first derivative:
dxs AUPs 1[  s AUPs 1  (1   s ) AUPs ]   s AUPs 1[ AUPs 1  AUPs ]

d s
[  s AUPs 1  (1   s ) AUPs ]2
(81)
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2.3.3. Property Integration
Rearranging and simplifying:
dxs
AUPs AUPs 1

d s [  s AUPs 1  (1   s ) AUPs ]2
(82)
From the previous development rule 2 is obtained:
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
Rule No. 2
“On
a
ternary
cluster
diagram,
minimization of the cluster arm of a source
corresponds to minimization of the flow
contribution of that source; minimum s
corresponds to minimum xs”
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
•Consider the case of fresh external source F,
the objective is to minimize its use. A process
internal stream W that can be recycled or
reused to reduce the use of F. It is desired to
mixed them in order to obtain a minimum cost
mixture that satisfy sink constraints, the feed to
the sink is subject to a number of property
constraints that can be mapped in a cluster
diagram as follows
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
Minimum distance,
this is a necessary
condition only. For
sufficiency
AUP
and flow rate must
be matched as well
Ci
W
a
Sink
b
Multiple
mixtures
c
F
Cj
Source : Component less design of recovery and allocation systems: a functionality based approach
Ck
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Ci
2.3.3. Property Integration
For multiple sources
the line connecting W1
and W2 represents the
possible mixtures, the
optimal mixing point
is the one that gives
the minimum s
W1
Multiple sources case:
W2
Sink
Multiple
mixtures
F
Cj
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Ck
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Ci
2.3.3. Property Integration
When the process
stream
W
target
cannot be met, the
stream
can
be
adjusted
via
an
interception device
e.g.
separation,
reaction etc
Adjusting properties
W
Wintercepted
Sink
Adjusting properties
will
change
the
cluster value
F
Cj
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
• For a selected mixing point and a desired s, the
fresh arm can be drawn to determine the desired
location of the desired location of Wintercepted.
Moreover, since the values of AUP are known for F
and the mixing point of the sink, one can plug the
targeted value of xF into Equation 78 to calculate
the desired value of AUP for Wintercepted. Once
Wintecepted and AUP are known, we can solve the
cluster equations backwards to calculate the raw
properties of Wintercepted
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• This is the minimum extent of interception to achieve
maximum recycle of W or minimum usage of F since the
additional interception will still lead to the same target or
minimum usage but will result in a mixing point inside the
sink and not just on the surrounding of the sink
• Once the task for interception is define, conventional
process synthesis techniques can be apply to develop
the design and operating parameters for the interception
system. The same procedure can be repeated for
multiple mixing points resulting in the task identification
of the locus for minimum extend to interception
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Ci
2.3.3. Property Integration
Locus
for
minimum extent
of interception
Locus Identification
W
Sink
F
Cj
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2.3.3. Property Integration
Multiplicity of Optimal values of AUP
A cluster point made of C1sink, C2sink, C3sink can correspond to multiple combinations
of properties that can give the same cluster values. As a result one can have
nMultiple, points within the feasible property domain giving a single cluster value.
Three conditions must be satisfied in order to insure feasibility of the sources or
mixture of sources going into a sink:
1. The cluster value of the source must be contain within the feasibility region of
the sink on the cluster diagram
2. The values of AUP for the source and the sink must match
3. The flow rate of the source must lie within the acceptable feed flow rate range
of the sink
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2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
From Rule No. 1 minimizing xs will minimize CostMixture, therefore we need
to select an AUPm (given for the feasible properties p1,m, p2,m, p3,m) that will
be minimized by the following relationship between AUPm and xs.
AUPm  AUPs 1
xs 
AUPs  AUPs 1
(83)
therefore
xs
1

AUPm
AUPs  AUPs 1
Source : Component less design of recovery and allocation systems: a functionality based approach
(84)
204
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
To minimize xs and as a result the cost we should select:
optimum
m
AUP
 Arg min AUPm if
AUPmoptimum  Arg max AUPm if
AUPs  AUPs 1
(85)
AUPs  AUPs 1 (86)
If no mixture matches the AUP selected for the sink for the case given by
Equation 84 then one has to decrease the value of the sink’s AUP starting with
Argmax AUPm till getting the highest value of AUPm within the feasible range
of AUP which matches that of the mixture; same procedure is used for
Equation 85, by increasing the value of sink’s AUP starting with Argmin AUPm
till getting the highest value contained within the feasible range of the sink
which matches that of the mixture
205
Source : Component less design of recovery and allocation systems: a functionality based approach
Texas A&M University
2. Foundation Elements
2.3. Overview of Mass, Energy and Property Integration
2.3.3. Property Integration
Currently research is being undertaken to design tools that will
cover cases for 1, 2 and more than three properties. This is a
very dynamic and changing field of research
206
Source : Component less design of recovery and allocation systems: a functionality based approach
Texas A&M University
TIER II
207
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• A tire to fuel processing plant flow sheet is shown in the
next slide which is a more complete description for the
one given in Example 2. Tire shredding is achieved by
using high pressure water jets. The shredded tires are fed
to the process while the spent water is filtered. The wet
cake collected from the filtration system is forwarded to
solid waste handling.
• The filtrate is mixed with 0.20 kg/s of fresh water makeup
to compensate for water losses with the wet cake, 0.08 kg
water/s and the shredded tires 0.12 kg water/s. The
mixture of filtrate and water make up is fed to a high
pressure compression station for recycling the shredding
unit. Due to the pyrolisis reactions, 0.08kg water is
208
generated
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• The plant has two primary sources for waste
water, the decanter (0.20 kg water/s and the
seal pot 0.15 kg/s. The plant has been
shipping the waste water for off-site
treatment.
The
cost
of
wastewater
transportation and treatment is $0.02/kg
leading to a wastewater treatment cost of
approximately $129,000/yr
209
Texas A&M University
3. Case Study
Tire to Fuel Plant
Flow Sheet
Condenser
Reactor OffGases
Tires
Water Jet
Shredding
Shredded
Tires
Filtration
Compression
Gaseous
Fuel
Flare
Waste water to
treatment 0.20 kg/s
500 ppmw
Decanter
Light
Oil
Pyrolisis
Reactor
To
Atmosphere
Separation
Fresh
water
0.15 kg/s
0 ppmw
Seal
Pot
Waste water to
treatment, 0.15 kg/s
0 ppmw
Flare Gas, 0.15 kg/s
200 ppmw
Finishing
Liquid
Fuel
Wet Cake to Solid Handling
0.08 kg/s, 0 ppmw
Fresh Water
0.20 kg/s
0
ppmw
210
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
•
The plant wishes to stop off site treatment of wastewater to avoid
the cost ($129,000/yr) and alleviate legal liability concerns in case
of transportation accident or inadequate treatment of wastewater
treatment. For capital budget authorization, the plant has the
following economic criteria:
Fixed capital investment
Payback period 
 4 years
Annual Savings
Annual Savings  Annual avoided cost off -site treatment Annual operating cost on-sitesystem
211
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
Economic Data
• Fixed cost of extraction system associated with S2. $ = 130,000
(flow rate of wastewater, kg/s)0.60
• Fixed cost of adsorption system associated with S3, $ = 800,000
(flow rate of wastewater, kg/s)0.72
• Fixed cost of stripping system associated with S4, $ = 280,000
(flow rate of wastewater, kg/s)0.66
• A biotreatment facility that can handle 0.35kg/s waste water has a
fixed cost of $260,000 and an annual operating cost of $72,000/yr
Technical Data
• Water may be recycle to two sinks: the seal pot and the water-jet
212
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
Compression station. The following constrains on flow rate and
composition of the pollutant (heavy organic) should be satisfied:
Seal Pot
• 0.10  Flow rate of feed water (kg/s)  0.20
• 0  Pollutant content of feed water (ppmw)  500
Make up to water-jet compression station
• 0.18  Flow rate of make up water (kg/s)  0.20
• 0  Pollutant content of make up water (ppmw)  50
213
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
Solution
We will start with an overall mass balance, note that 0.12 kg/s of
water are lost in the process and cannot be re used
0.2 kg/s to
Compression
Station
0.15 kg/s to
Seal Pot
0.08 kg/s from
Wet Cake
Water Generation
0.08kg/s
0.15 kg/s from
Seal Pot
0.2 kg/s from
Decanter
214
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
Solution
From the overall mass balance we can set the targets for fresh use and
wastewater production
0.2 kg/s
No
Fresh
Water
0.15 kg/s
0.08 kg/s
Water Generation
0.08kg/s
0.35 kg/s
0.08 kg/s
Wastewater
The source diagram is shown in the next slide
215
Texas A&M University
3. Case Study
kg/s
Source/Sink Diagram
0.22
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
WW from
Decanter
Compression Station
WW from
Seal Pot
Seal Pot
WW from Wet
Cake
0
50
100
150
200
250
300
350
400
450
500
550
ppmw
216
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• From the source/sink diagram we can
see that wastewater from the decanter
can be accepted by the seal pot only;
the
outlet
composition
of
the
wastewater coming from the seal pot is
400 ppmw (from the pinch diagram) as
shown in Example 2
217
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
Mass
Exchanged
10-6
Pinch Diagram
200
150
100
50
Composition
from Seal Pot
0
0
100
200
300
400
500
600
218
Texas A&M University
3. Case Study
kg/s
Source/Sink Diagram
0.22
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
W W from
Decanter
W W from Seal Pot
Compression Station
Seal Pot
W W from Wet Cake
0
50
100 150
200 250
300 350
ppmw
400 450
500 550
219
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• Wastewater coming from the seal pot
cannot be recycled directly to the
compression station due to its high
pollutant composition, therefore it is
required to treat it using an external
MSA as shown in Example 2; for this
case S4 is the best stripping agent,
which will bring down the composition
to 50ppmw
220
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
kg/s
Source/Sink Diagram
0.22
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
WW from Stripper
WW from
Decanter
WW from Seal Pot
Compression Station
Seal Pot
WW from Wet Cake
0
50
100
150
200
250
300
ppmw
350
400
450
500
550
221
Texas A&M University
3. Case Study
Tire to Fuel Plant
Flow Sheet (Revised)
Condenser
Reactor OffGases
Tires
Water Jet
Shredding
Shredded
Tires
Filtration
Compression
Gaseous
Fuel
Flare
Decanter
Light
Oil
Pyrolisis
Reactor
To
Atmosphere
Separation
Seal
Pot
Stripper
Flare
Gas
Finishing
Liquid
Fuel
Wet Cake to Solid Handling
222
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• Now we will proceed to compare the different
alternatives in order to make a decision. For the
bio-treatment plant we have:
Annualized Saving Cost = $129,000/yr - $72,000/yr = $57,000/yr
Pay Back = $260,000 / $57,000/yr = 4.56 years
• For the recycling/stripping system:
Annualized Saving Cost = $129,000/yr - $84,270.5/yr = $44,729.5/yr
Fixed Cost of Stripping = $280,000(0.2)0.66 = $96,791.6
Pay Back = $96,791.6 / $44,729.5/yr = 2.16 years
223
Texas A&M University
3. Case Study
3.1. Tire to Fuel Processing Plant
• From the results we can conclude that the
recycling/stripping alternative is the best
economical and technical option. We need
to point out that the water contained in the
wet cake will not be recovered or treated
224
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
• Wood chips are chemically cooked in a Kraft digester using
a white liquor (mainly NaOH and Na2S). Black liquor (spent
white liquor) is converted back to white liquor by a recovery
cycle. The digested pulp is then bleached to obtain
bleached pulp (fiber I). The plant also buys pulp from
another plant (fiber II), the pulp is then sent to two different
paper machines (Sink I and Sink II). Paper machine I uses
200 tons/hr of fiber I. A mix of fiber I and II (20 ton/hr and
30 ton/hr, respectively) is fed to paper machine II. Due to
interruptions and other disturbances, a certain amount of
partly and completely manufactured paper is rejected
225
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
• The rejected fiber is referred as broke, which is passed
through a hydro-pulper and a hydro-sieve resulting in two
streams, an underflow which is burnt and an overflow
which goes to waste treatment. Part of the broke contains
fiber which can be recycle for paper making.
• The properties that are important for the process are:
– Objectionable material (OM), undesirable material in the fiber
– Reflectivity (R), reflectance of an infinite thick material
compared to a standard
– Absorption coefficient (k), measure of absorptivity of light into
the fibers
226
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
• The mixing rules are:
OM   x OM s
Ns
s 1 s
2
 m2 

m 
Ns
   s 1 xs k s 

k 
 g 
 g 
6

R  x R
Ns
s 1 s
6
s
227
Texas A&M University
3. Case Study
OM =0.0
Wood
Chips
k = 0.0012
Pulp
Kraft Digester
White
Liquor
Fiber I
R = 0.85
Bleaching
Black
Liquor
Broke
(Overflow)
200 t/hr
Paper I
Paper
Machine I
OM =0.085
k = 0.0013
Reject
R = 0.95
20 t/hr
Chemical
Recovery
Cycle
HydroSieve
HydroPulper
Underflow
Fiber II
OM =0.0
30 t/hr
k = 0.00065
R = 0.95
Paper
Machine II
Reject
Paper II
228
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
Constraints for Paper Machine I, (Sink I)
Property
Lower Bound Upper Bound
OM (mass fraction)
0
0.03
k (m2 / gm)
0.00115
0.00125
R
0.85
0.95
Flowrate (ton/hr)
95
100
Constraints for Paper Machine II, (Sink II)
Property
Lower Bound Upper Bound
OM (mass fraction)
0
0
k (m2 / gm)
0.0007
0.00125
R
0.9
0.95
Flowrate (ton/hr)
45
45
229
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
Properties of Fiber Sources
OM
Source
(mass
Broke
Fiber I
Fiber II
fraction)
0.085
0
0
k (m2 / gm)
0.0013
0.0012
0.00065
R
0.95
0.85
0.95
Maximum
Available
Flowrate
(ton/hr)
35


Cost
($/ton)
0
230
395
230
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
1. Determine the optimal allocation of the
three sources, fiber I, II and broke for a
direct recycle reuse without new equipment
2. In order to maximize use of process
resources and minimize wasteful discharge
(broke) how should the designer change
the properties of the broke as to achieve
maximum recycle?
231
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
Solution
In order to translate the data from property domain to cluster
domain we will select arbitrarily reference values as:
OM
k
ref
ref
 0.02
 0.001m / gm
2
R  1.0
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
We will proceed to calculate the cluster values for the
sources as follows:
Source
Broke
Fiber I
Fiber II
OM
0.085/0.02
0
0
k
R
6 6
0.0013/0.001 0.95 /1
6 6
0.0012/0.001 0.85 /1
6 6
0.00065/0.001 0.95 /1
AUPBroke  OM   k   R  4.25  1.3  0.73  6.28
AUPFiber I  OM   k   R  0  1.2  0.377  1.577
AUPFiber II  OM   k   R  0  0.65  0.73  1.38
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
4.25
COM , Broke 
 0.677
6.28
1.3
Ck , Broke 
 0.21
6.28
0.735
C R , Broke 
 0.12
6.28
Similarly for Fiber I and II we obtain:
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
0
COM , Fiber I 
0
1.577
1.2
Ck , Fiber I 
 0.761
1.577
0.377
C R , Fiber I 
 0.239
1.577
0
COM , Fiber II 
0
1.38
0.65
Ck , Fiber II 
 0.471
1.38
0.735
C R , Fiber II 
 0.533
1.38
Now we can proceed to transform the ternary points to X vs. Y plot
235
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
YBroke  0.866COM , Broke  0.586
X Broke  1  Ck , Broke  0.5COM , Broke  0.452
YFiber I  0.866COM , Fiber I  0
X Fiber I  1  Ck , Fiber I  0.5COM , Fiber I  0.239
YFiber II  0.866COM , Fiber II  0
X Fiber II  1  Ck , Fiber II  0.5COM , Fiber II  0.530
236
Texas A&M University
Ternary / X-Y Diagram
1
COM
Y
0.8
0.6
Broke
0.4
0.2
Fiber I
Fiber II
0
Ck
CR
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
X
237
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
• Now we need to proceed to locate sinks in the diagram by
using the point illustrated in slide 187
For Sink I:
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
max
min
min
max
min
min
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
max
max
min
max
max
min
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
min
max
min
min
max
min
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 max
 0.03 / 0.2  0.15
OM , S in k I
 k ,S in k I  0.00115 / 0.001  1.15
min
6
6
 min

0
.
85
/
1
.
0
 0.377
R , S in k I
AUP  1.677
max
COM
, Sink I  0.15 / 1.677  0.09
C kmin
, Sink I  1.15 / 1.677  0.681
max
COM
, Sink I  0.377 / 1.677  0.229
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 max
 0.03 / 0.2  0.15
OM , S in k I
 k ,S in k I  0.00125 / 0.001  1.25
max
6
6
 min

0
.
85
/
1
.
0
 0.377
R , S in k I
AUP  1.777
max
COM
, Sink I  0.15 / 1.777  0.084
C kmin
, Sink I  1.25 / 1.777  0.703
max
COM
, Sink I  0.377 / 1.777  0.213
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 min
 0 / 0 .2  0
OM , S in k I
 k ,S in k I  0.00125 / 0.001  1.25
max
6
6
 min

0
.
85
/
1
.
0
 0.377
R , S in k I
AUP  1.627
max
COM
, Sink I  0 / 1.627  0
C kmin
, Sink I  1.25 / 1.627  0.77
max
COM
, Sink I  0.377 / 1.627  0.23
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
For Sink I, continuation:
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
max
min
max
max
min
max
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
min
min
max
min
min
max
( i ,s ,  j ,s ,  k ,s )  ( OM ,S in kI ,  k ,S in kI ,  R ,S in k I )
min
max
max
min
max
max
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 max
 0.03 / 0.2  0.15
OM ,S in k I
 min
 0.00115 / 0.001  1.15
k ,S in k I
R
max
 , S in k I
 0.95 / 1  0.735
6
6
AUP  2.035
C
max
OM , Sink I
 0.15 / 2.035  0.074
Ckmin
, Sink I  1.15 / 2.035  0.565
C Rmax
 0.735 / 2.035  0.361
 , Sink I
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 min
 0 / 0.2  0
OM ,S in k I
 min
 0.00115 / 0.001  1.15
k ,S in k I
R
 0.95 / 1  0.736
max
6
 ,S in k I
6
AUP  1.886
C
min
OM , Sink I
C
min
k , Sink I
C
min
R , Sink I
 0 / 1.886  0
 1.15 / 1.886  0.61
 0.736 / 1.886  0.39
244
Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
 min
 0 / 0.2  0
OM , S in k I
 max
 0.00125 / 0.001  1.25
k , S in k I
R
 0.95 / 1  0.736
max
6
 , S in k I
6
AUP  1.986
C
min
OM , Sink I
C
min
k , Sink I
C
min
R , Sink I
 0 / 1.986  0
 1.25 / 1.986  0.63
 0.736 / 1.986  0.37
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Texas A&M University
COM
Ck
Xsink I
Ysink I
0.210
0.761
0.471
0.681
0.703
0.770
0.565
0.610
0.630
0
1
0.5
0.452
0.239
0.529
0.274
0.255
0.230
0.398
0.390
0.370
0
0
0.866
0.586
0.000
0.000
0.078
0.073
0.000
0.064
0.000
0.000
Sink I and Sources
Y
1
0.9
0.8
0.7
0.6
Broke
0.5
0.4
0.3
0.2
0.1
0
Ck
0.677
0.000
0.000
0.090
0.084
0.000
0.074
0.000
0.000
COM
Fiber II
CR
0
0.1
Fiber I
0.2
0.3
0.4
0.5
X
0.6
0.7
Sink I
0.8
0.9
1
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Texas A&M University
3. Case Study
3.2. Pulp and Paper Process Plant
• Similarly for Sink II we have:
Sink II
OM
k
R
F
OMMin OMMax
0
0
Low High
0
0
0.0007 0.001
0.9
0.95
45
45
kMin
0.7
kMax
1.25
RMin
0.531441
Ref
0.02
0.001
1
RMax
0.735092
COM
Ck
0.677
0.000
0.000
0.090
0.084
0.000
0.074
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.210
0.761
0.471
0.681
0.703
0.770
0.565
0.610
0.630
0.568
0.702
0.702
0.488
0.488
0.630
Xsink I
0
1
0.5
0.452
0.239
0.529
0.274
0.255
0.230
0.398
0.390
0.370
0.432
0.298
0.298
0.512
0.512
0.370
Ysink I
0
0
0.866
0.586
0.000
0.000
0.078
0.073
0.000
0.064
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
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Sink I - II and Sources
1
COM
0.9
0.8
0.7
Broke
Y
0.6
0.5
Sink II
0.4
0.3
0.2
0.1
Fiber I
Fiber II
0
Ck
0
Sink I
0.1
0.2
0.3
0.4
0.5
X
0.6
0.7
0.8
0.9
1
CR
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Now we proceed
to identify the
minimum distance
for Sink I, that will
minimize the use
of fresh sources
Sink I and Sources
3.2. Pulp and Paper Process Plant
Y
1
0.9
0.8
0.7
0.6
COM
Broke
0.5
0.4
0.3
0.2
0.1
0
Ck
Fiber II
CR
0
0.1
Fiber I
0.2
0.3
0.4
0.5
X
0.6
0.7
Sink I
0.8
0.9
1
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In order to get the
length of the arm to
obtain s one can
measure it from the
graph or:
Sink I - II and Sources
1
COM
0.9
d  ( x1  x2 ) 2  ( y1  y2 ) 2
0.8
or
0.7
Y
0.6
By Equation 65
0.5
0.4
0.3
0.2
0.1
0
Ck 0
(0.27, 0.85)
0.1
0.2
0.3
0.4
0.5
X
0.6
0.7
0.8
0.9
1
CR
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3. Case Study
3.2. Pulp and Paper Process Plant
The distance between mixture and broke is:
d  ( x1  x2 )  ( y1  y2 )
2
2
d  (0.27  0.452) 2  (0.085  0.586) 2
d  0.533
The Total distance is:
d  (0.452  0.239) 2  (0.586  0) 2
d  0.623
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3. Case Study
3.2. Pulp and Paper Process Plant
Therefore s is:
 Fiber I
0.533

 0.855
0.623
Using Equation 65:
C OM Mixture   BrokeCOM , Broke   Fiber I COM , Fiber I
 Fiber I 
C OM Mixture  COM , Broke
COM , Fiber I  COM , Broke
0.098  0.677

 0.855
0  0.677
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3. Case Study
3.2. Pulp and Paper Process Plant
From Equation 86, AUPmoptimum = 2.035
X Fiber I
2.035
 0.855
 1.103
1.577
Therefore xs is:
C OM Mixture   BrokeCOM , Broke   Fiber I COM , Fiber I
 Fiber I 
C OM Mixture  COM , Broke
COM , Fiber I  COM , Broke
0.098  0.677

 0.855
0  0.677
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TIER III
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4. Open Ended Problem
An ethylene/ethyl benzene plant is shown in the next flow sheet. Gas oil
is being cracked with steam in a pyrolysis furnace to form ethylene, low
BTU gases, hexane, heptanes, and heavier hydrocarbons. The ethylene
is then reacted with benzene to form ethyl benzene. Two waste water
streams are formed one of the streams is the quench water recycle for
the cooling tower and the second one is the waste water from the ethyl
benzene portion of the plant. The primary pollutant present in the two
waste water streams in benzene. Benzene must be removed from the
waste water that will be use to quench the cooling tower, coming from the
settling unit to a concentration of 180ppm before it can be recycled back
to the cooling tower and the boiler water treatment process. Benzene
must also be removed from the waste water stream coming from the
lower separation unit down to a composition of 380ppm before the waste
water stream can be sent to biotreatment
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Fresh
Water
Gas
Oil
Pyrolysis
Furnace
Recycle Quenched
Water
Cooling
Tower
Low BTU gases
Hexane
0.8kg/s
10ppmw
Upper
Separation
Heptane
0.4kg/s
17ppmw
Steam
Heavy
Hydrocarbons
Benzene
Fresh
Water
Ethyl benzene
Reactor
Ethylbenzene
Boiler
Water
Treatment
Settling
Refuse
Vent Fuel
Waste
water
150kg/s
1100ppm
To
Biotreatment
Lower
Separation
Waste
water
70kg/s
2100ppm
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4. Open Ended Problem
The heptane and hexane streams will be used to recover part of the
benzene, the desired final composition of them is unknown and has to be
determined by the engineer, after which they are sent to finishing and
storage. The mass transfer driving forces e1 and e2, should be at least
25,000 and 29,000ppmw respectively. The equilibrium data for benzene
transfer from waste water to hexane (1) and heptane (2) are:
y = 0.012x1
y = 0.009x2
Where y, x1 and x2 are in mass fractions. Two external MSA are being
considered for removing of benzene; air and activated carbon. Air is
compressed to 2 atmospheres before stripping. Following stripping,
benzene is separated from air using condensation.
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4. Open Ended Problem
•
Henry’s law can be used to predict equilibrium for the
stripping process. Activated carbon is regenerated using
steam in a ratio of 2kg steam : 1 kg of benzene
adsorbed on activated carbon. Make up at a rate of
1.2% of recirculating activated carbon is needed to
compensate for losses due to regeneration and
deactivation. Over the operating range, the equilibrium
relation for the transfer of benzene from waste water
onto activated carbon can be described by:
y = 6.8x10-4x4
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4. Open Ended Problem
1.
2.
3.
4.
5.
Label the rich and lean streams
Construct a pinch diagram, identify pinch location,
minimum load of benzene to be removed by external
and excess capacity of MSA’s Consider the four MSA’s
to choose from and find the MOC needed to remove
benzene. Use the cost data found in slide 97
Apply the algebraic approach
Design the network for the plant and draw a modified
flow sheet
Comment on your results, what limitations do you think
have the methods used in the calculations if any, what
conclusions can you draw based on your results?
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5. Acknowledgments
I wish to thank for their cooperation and guidance:
•
•
•
•
•
•
•
Dr. Mahmoud M. El-Halwagi Professor Texas A&M
Dr. Jules Thibault Professor University of Ottawa
Dr John T. Baldwin Professor Texas A&M
Dr. Dustin and Georgina Harrel Texas A&M
Vasiliki Kazantzi PhD student Texas A&M
Qin Xiaoyun Researcher Candidate Texas A&M
Daniel Grooms PhD student Texas A&M
William Acevedo, April 2004
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References
• El-Halwagi M. Mahmoud, Pollution Prevention through Process
Integration Systematic Design Tool, Academic Press, 1997
• El-Halwagi M. Mahmoud, Glasgow M. Ian, Eden R. Mario, Qin
Xiaoyun, Property Integration: Componentless Design Techniques and
Visualization Tools, Texas A&M
• Kazantzi V., Harell D., Gabriel F., Qin X., El-Halwagi M.M., Property
Based Integration For Sustainable Design, AIChE Annual Meeting,
2003
• Seider D. Warren, Seader J.D., Lewin Daniel R., Product and Process
Design Principles, Wiley International, 2004, 2d ed
• Shelley, M.D. and El-Halwagi M.M., Component-less Design of
Recovery and Allocation Systems: A Functionality based Clustering
Approach, Computers and Chemical Engineering, 24, 2081-2091,
2000
• Qin X., Gabriel F., Harell D., El-Halwagi M.M., Algebraic Techniques
261
for Property Integration Via Componentless Design, Texas A&M